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Abstract

We use the number density distributions of K and M dwarf stars with vertical height from the Galactic disk, determined using observations from the Sloan Digital Sky Survey, to probe the structure of the Milky Way disk across the survey's footprint. Using photometric parallax as a distance estimator we analyze a sample of several million disk stars in matching footprints above and below the Galactic plane, and we determine the location and extent of vertical asymmetries in the number counts in a variety of thin- and thick-disk subsamples in regions of some 200 square degrees within 2 kpc in vertical distance from the Galactic disk. These disk asymmetries present wave-like features as previously observed on other scales and at other distances from the Sun. We additionally explore the scale height of the disk and the implied offset of the Sun from the Galactic plane at different locations, noting that the scale height of the disk can differ significantly when measured using stars only above or only below the plane. Moreover, we compare the shape of the number density distribution in the north for different latitude ranges with a fixed range in longitude and find the shape to be sensitive to the selected latitude window. We explain why this may be indicative of a change in stellar populations in the latitude regions compared, possibly allowing access to the systematic metallicity difference between thin- and thick-disk populations through photometry.

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Digital Object Identifier (DOI)

https://doi.org/10.3847/1538-4357/aa77fd

Funding Information

This manuscript evolved from D.F.'s 2016 May senior honors thesis at the University of Kentucky, and she acknowledges the support of The University of Kentucky Singletary Scholarship as well as an Undergraduate Summer Research Fellowship from the University of Kentucky during its completion.

D.F. and S.G. acknowledge partial support from the U.S. Department of Energy under contract DE-FG02-96ER40989.

Funding for the Sloan Digital Sky Survey has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah.